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Minimizing the Disruption of Traffic Flow of Automated Vehicles During Lane Changes
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Minimizing the Disruption of Traffic Flow of Automated Vehicles During Lane Changes

Category : RTOS


Sub Category : Automation


Project Code : ITROS06


Project Abstract

Introduction:

Vehicles that are becoming more highly automated are revolutionizing the world’s transportation systems for their promise of increased safety and efficiency. The advantage of vehicles incorporating automation is that they do not suffer from the same limitations as human drivers, such as being distracted or impaired. In order to realize the potential of these vehicles, which operate in highly dynamic environments, online techniques are needed. This paper presents such an algorithm to minimize the disruption of traffic flow by optimizing for the number of safe lane

changes, thereby increasing throughput and reducing congestion. The proposed algorithm is distributed in nature and makes use of vehicle-to-vehicle and/or vehicle-to-infrastructure communication technologies to judiciously make local lane-change decisions while guaranteeing that no collisions will occur. In contrast to existing work, the proposed technique requires no assumption on the number of lanes, nor on the dynamic attributes of the vehicles such as velocity and acceleration. Simulation results show that the proposed algorithm is both efficient and effective in maximizing the number of lane changes on a given stretch of a highway.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Existing System:

Proposed System:

    There is not such a system to monitor the speed, type and number of vehicles in roads.

 

 

 

Drawbacks of existing system

 

     Manual monitoring

    Camera monitoring is not helpful in fog weather conditions

   Not able to count  the number of vehicles

 

    Here we are proposingsensor based vehicle counting, type and speed of the vehicle

   The monitored data is send to control section and data’s are stored

 

Advantages of proposed system

 

     Fully automatic

     Particular vehicles data’s are stored under its vehicle number

    Type of vehicle is found automatically

    The speed is measured using sensor

 
 
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